Abstract

Target tracking is a critical important part in robot controlling system and it usually cannot get satisfied results because of the complex condition. The Kalman Forecast Algorithm on the camera platform which has two degrees of freedom has been researched in this paper. The motion model has been built based on the particular characteristic of the target tracking system. An extend kalman filter algorithm has been made up on this paper for this nonlinear model to dynamically compensate the error in line procession. The results show that the new algorithm can get fine effect in control of noise, time and punctual. And it meets the requirement of real-time target tracking. Therefore, a great value of application is showing up.

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Acknowledgments

This paper is supported by the national natural science fund project of Hubei province (number: 2010CDB02504), and the national natural science fund major project of Hubei province (number: 2010CBB0800).